Evidence map›Paper›PMID 32875928›Full record

ArticleGlobal spine journal2021

Artificial Intelligence and Robotics in Spine Surgery.

Jonathan J Rasouli, Jianning Shao, Sean Neifert, Wende N Gibbs, Ghaith Habboub, Michael P Steinmetz, Edward Benzel, Thomas E Mroz

Open access · goldAbstract read
In one paragraph

Article in Global spine journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 2 pooled it
5.6field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

48 citing papers in PubMed, 2 syntheses or guidelines pooled it, 129 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Global analysis and prospects of assisted pedicle screw placement surgery: a bibliometric study.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
    Article
  5. Intraoperative full-spine imaging with C-arm using a deep learning-based automatic stitching model: development and clinical validation.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
    Article
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  18. Artificial intelligence: revolutionizing robotic surgery: review.Annals of medicine and surgery (2012) · 2024
    Review
  19. [Brief history and application prospect of robotic spine surgery].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2024
    Article
  20. Robotic-assisted spine surgery-a narrative review.Journal of spine surgery (Hong Kong) · 2024
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Jonathan J Rasouli2569Cleveland Clinic, Cleveland, OH, USA.ORCID https://orcid.org/0000-0002-5085-8422
Jianning Shao2569Cleveland Clinic, Cleveland, OH, USA.
Sean Neifert5925Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Wende N Gibbs384840Mayo Clinic Scottsdale, Scottsdale, AZ, USA.
Ghaith Habboub2569Cleveland Clinic, Cleveland, OH, USA.
Michael P Steinmetz2569Cleveland Clinic, Cleveland, OH, USA.
Edward Benzel2569Cleveland Clinic, Cleveland, OH, USA.
Thomas E Mroz2569Cleveland Clinic, Cleveland, OH, USA.
Cleveland Clinic · USIcahn School of Medicine at Mount Sinai · USMayo Clinic in Arizona · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

STUDY

designNarrative review.

objectivesArtificial intelligence (AI) and machine learning (ML) have emerged as disruptive technologies with the potential to drastically affect clinical decision making in spine surgery. AI can enhance the delivery of spine care in several arenas: (1) preoperative patient workup, patient selection, and outcome prediction; (2) quality and reproducibility of spine research; (3) perioperative surgical assistance and data tracking optimization; and (4) intraoperative surgical performance. The purpose of this narrative review is to concisely assemble, analyze, and discuss current trends and applications of AI and ML in conventional and robotic-assisted spine surgery.

methodsWe conducted a comprehensive PubMed search of peer-reviewed articles that were published between 2006 and 2019 examining AI, ML, and robotics in spine surgery. Key findings were then compiled and summarized in this review.

resultsThe majority of the published AI literature in spine surgery has focused on predictive analytics and supervised image recognition for radiographic diagnosis. Several investigators have studied the use of AI/ML in the perioperative setting in small patient cohorts; pivotal trials are still pending.

conclusionsArtificial intelligence has tremendous potential in revolutionizing comprehensive spine care. Evidence-based, predictive analytics can help surgeons improve preoperative patient selection, surgical indications, and individualized postoperative care. Robotic-assisted surgery, while still in early stages of development, has the potential to reduce surgeon fatigue and improve technical precision.

Indexed as

artificial intelligencemachine learningradiologyreviewrobotic spine surgeryspine surgery

Identifiers

PMID32875928
PMCPMC8119909
OpenAlexW3014788674

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.